. Istanbul 2004
ied, the results
refer to three
to the original
accuracy.
ng (13) at all
esulting curve
xt finer scale.
vailable in the
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004
Figure 4. Convergence of the snake at increasing scale
The whole process is rapidly convergent. The final result is
shown below. Comparison with ground truth is currently under
way.
Figure 5. Snake at original image
5. CONCLUSION
We have employed an algorithm which utilizes a modified
version of the active contour model, using a class of external
forces defined by the negative of the modulus of wavelet
transform of the image. The wavelet-based active contour
model combine wavelet decomposition and edge detection in a
single procedure. It has been applied to SAR sateilite images to
determine the coastline. Obtained results are encouraging, and
further tests are in progress.
ACKNOWLEDGMENTS
The work described in the present paper has been funded in
part through project 23 of CIPE-MIUR CLUSTER 22.
REFERENCES
Cohen, L.D., 1991. On Active Contour Models and Balloons.
Computer Vision and Image Processing. Image Understanding,
53(2), pp.211-218.
Cohen, I., Cohen, L., and Ayache, N., 1992. Using deformable
surface to segment 3-D images and infer differential structures.
Computer Vision, Graphic and Image Processing: image
understanding, 56(2), pp. 242-263.
Cohen, L.D., and kimmel, R., 1997. Global minimum for
Active Contour Models: a minimal path approach. /nt. Journal
of Computer Vision, 24(1), pp.57-78.
Dohono, D.L.,1995. De-noising by soft thresholding. /EEE
Trans. Inform. Theory, 41(3), pp. 6113-627.
Durikovic, R., Kaneda, K., and Yamashita, H., 1995. Dynamic
contour: a texture approach and contour operations. The visual
Computer, 11, pp.277-289.
Hug, J., Brechbuhler, C., and Szekely, G., 1999. Tamed snake:
a particle system for robust semi-automatic segmentation.
Second International Conference on Medical Images
computing and Computer-assisted intervention (MICCAI'99),
Cambridge, number 1679, pp. 106-115.
Kass, M.. Witkin, A., and Terzopoulos, D., 1987. Snakes:
Active contour models. /nt. Journal of Computer Vision, 1(4),
pp. 321-331.
Leymarie, F., and Levine, M.D.,1993. Tracking deformable
objects in the plane using an active contour model. /EEE Trans.
PAMI, pp. 617-634.
Leroy, B., Herlin, L, Cohen, L.D., 1996. Multi-resolution
algorithms for active contour models. Proc. 12" International
Conference on Analysis and Optimization of Systems, pp. 58-
65.
Liu, J.C., and Hwang, W.L., 2002. Active Contour Model using
wavelet modulus for object segmentation and tracking in video
sequences. Int. Journal of Wavelets, Multiresolution and
Information Processing, 1(1), pp.93-113.
Mallat, S., and Hwang, W.L., 1992. Singularity detection and
processing with wavelets. [EEE Trans. on Information Theory,
38(2) pp.617-643.
Mallat, S., and Zhong, S., 1992. Characterization of signals
from multiscale edges. /EEE Trans. PAMI, pp.710-732.
Madchakham, S., Thitimajshima, P., and Rangsanseri, Y., 2001.
Edge detection in speckled SAR images using wavelet
decomposition. Proc. XXII Asian Conference on Remote
Sensing, Singapore. pp. 254-257.